In recent years, techniques for virtualizing networks and their functions are intensively researched. In such a network virtualization technique, a physical infrastructure provider (InP) allocates a different physical resource to each virtual network in accordance with a resource request from a virtual network service provider (VNSP). This makes it possible to completely isolate each virtual network, and each VNSP can individually provide services and manage resources by using the resources on the virtual networks constructed on a common physical infrastructure.
It is speculated that the rapid spread of the Internet of Things (IoT) leads to increased diversification of data generating devices including, for example, personal computers (PCs), smartphones, vehicles, sensors, and robots and of the requirements for the quality of service (QoS). In particular, the increasing number of mobile terminals makes it necessary for VNSPs to have mechanisms that automatically recognize unexpectedly changing network use environments (e.g., traffic load, occurrence of failure or emergency incident) or diversifying service requirements with an edge computing platform or the like and that automatically and promptly select and secure resources suitable in a given situation for each virtual network.
However, the current network construction involves many manual operations in resource allocation, identification number allocation, configuration, management, and so on. These processes need to be automated in order to reduce network configuration time, human errors, and so on.
Thus, methods of allocating resources to virtual networks are proposed to date. In particular, P. Skoldstrom and K. Yedavalli, “Network Virtualization and Resource Allocation in OpenFlow-based Wide Area Networks,” IEEE ICC 2012, Ottawa, Canada, pp. 6622-6626, June 2012 proposes a method that is based on a framework for OpenFlow (FlowSpace). Also, F. Esposito and I. Matta, “A Decomposition-Based Architecture for Distributed Virtual Network Embedding,” ACM SIGCOMM Workshop on Distributed Cloud Computing (DCC'14), Chicago, Ill., USA, pp. 53-58, August 2014 proposes a method that is based on mathematical programming, and X. Liu, P. Juluri and D. Medhi, “An Experimental Study on Dynamic Network Reconfiguration in a Virtualized Network Environment Using Autonomic Management,” IFIP/IEEE IM 2013, Ghent, Belgium, pp. 616-622, May 2013 proposes a resource allocation method that is based on the geographical locations of routers. However, with the resource allocation methods disclosed in Skoldstrom et. al., Esposito et. al., and Liu et. al., the virtual resource selection policy with respect to the virtual network construction request is fixed. In other words, the standard for determining how much and what type of virtual resources are to be allocated with respect to a given service requirement is fixed. Thus, the policy may not always be optimal in terms of assuring the quality of service and efficiently using the resources when an unexpected change in the network use environment occurs. If, in order to assure the quality of service, the virtual resource selection policy is to be determined and modified through manual and complex calculation processes each time the network use environment changes, the processing time increases, and the labor burden increases. These things make the implementation difficult.
When traffic congestion caused by an accident in logistics, security increase in a specific area, a natural disaster, a building collapse, an entertainment event, or the like occurs suddenly, there may arise a problem in that the quality of service is not assured due to a shortage of resources in an amount necessary for handling such an incident. In addition, with regard to a virtual network construction request requiring a high level of quality of service, the quality of service needs to be assured by automatically and quickly selecting and securing a virtual resource suitable for a given situation. In other words, a VNSP needs to be able to perform proactive control so that a virtual resource suitable for the service requirement or the use environment of the virtual network can be selected even when an emergency incident or a sudden traffic change occurs.
In addition to the above described problems, the techniques disclosed in Skoldstrom et. al., Esposito et. al., and Liu et. al. center on the technique pertaining to resource allocation of nodes and links in a network, and Skoldstrom et. al., Esposito et. al., and Liu et. al. are silent as to the selection and allocation of resources including computer resources, such as servers that conduct data processing, in a large-scale network constituted by an edge network, a core network, and a data center.